Cargando…

Reliability of the ASA Physical Status Classification System in Predicting Surgical Morbidity: a Retrospective Analysis

The American Society of Anesthesiologists (ASA) Physical Status Classification System has been used to assess pre-anesthesia comorbid conditions for over 60 years. However, the ASA Physical Status Classification System has been criticized for its subjective nature. In this study, we aimed to assess...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Gen, Walco, Jeremy P., Mueller, Dorothee A., Wanderer, Jonathan P., Freundlich, Robert E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8298361/
https://www.ncbi.nlm.nih.gov/pubmed/34296341
http://dx.doi.org/10.1007/s10916-021-01758-z
_version_ 1783726045004824576
author Li, Gen
Walco, Jeremy P.
Mueller, Dorothee A.
Wanderer, Jonathan P.
Freundlich, Robert E.
author_facet Li, Gen
Walco, Jeremy P.
Mueller, Dorothee A.
Wanderer, Jonathan P.
Freundlich, Robert E.
author_sort Li, Gen
collection PubMed
description The American Society of Anesthesiologists (ASA) Physical Status Classification System has been used to assess pre-anesthesia comorbid conditions for over 60 years. However, the ASA Physical Status Classification System has been criticized for its subjective nature. In this study, we aimed to assess the correlation between the ASA physical status assignment and more objective measures of overall illness. This is a single medical center, retrospective cohort study of adult patients who underwent surgery between November 2, 2017 and April 22, 2020. A multivariable ordinal logistic regression model was developed to examine the relationship between the ASA physical status and Elixhauser comorbidity groups. A secondary analysis was then conducted to evaluate the capability of the model to predict 30-day postoperative mortality. A total of 56,820 cases meeting inclusion criteria were analyzed. Twenty-seven Elixhauser comorbidities were independently associated with ASA physical status. Older patient (adjusted odds ratio, 1.39 [per 10 years of age]; 95% CI 1.37 to 1.41), male patient (adjusted odds ratio, 1.24; 95% CI 1.20 to 1.29), higher body weight (adjusted odds ratio, 1.08 [per 10 kg]; 95% CI 1.07 to 1.09), and ASA emergency status (adjusted odds ratio, 2.11; 95% CI 2.00 to 2.23) were also independently associated with higher ASA physical status assignments. Furthermore, the model derived from the primary analysis was a better predictor of 30-day mortality than the models including either single ASA physical status or comorbidity indices in isolation (p < 0.001). We found significant correlation between ASA physical status and 27 of the 31 Elixhauser comorbidities, as well other demographic characteristics. This demonstrates the reliability of ASA scoring and its potential ability to predict postoperative outcomes. Additionally, compared to ASA physical status and individual comorbidity indices, the derived model offered better predictive power in terms of short-term postoperative mortality.
format Online
Article
Text
id pubmed-8298361
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Springer US
record_format MEDLINE/PubMed
spelling pubmed-82983612021-08-12 Reliability of the ASA Physical Status Classification System in Predicting Surgical Morbidity: a Retrospective Analysis Li, Gen Walco, Jeremy P. Mueller, Dorothee A. Wanderer, Jonathan P. Freundlich, Robert E. J Med Syst Systems-Level Quality Improvement The American Society of Anesthesiologists (ASA) Physical Status Classification System has been used to assess pre-anesthesia comorbid conditions for over 60 years. However, the ASA Physical Status Classification System has been criticized for its subjective nature. In this study, we aimed to assess the correlation between the ASA physical status assignment and more objective measures of overall illness. This is a single medical center, retrospective cohort study of adult patients who underwent surgery between November 2, 2017 and April 22, 2020. A multivariable ordinal logistic regression model was developed to examine the relationship between the ASA physical status and Elixhauser comorbidity groups. A secondary analysis was then conducted to evaluate the capability of the model to predict 30-day postoperative mortality. A total of 56,820 cases meeting inclusion criteria were analyzed. Twenty-seven Elixhauser comorbidities were independently associated with ASA physical status. Older patient (adjusted odds ratio, 1.39 [per 10 years of age]; 95% CI 1.37 to 1.41), male patient (adjusted odds ratio, 1.24; 95% CI 1.20 to 1.29), higher body weight (adjusted odds ratio, 1.08 [per 10 kg]; 95% CI 1.07 to 1.09), and ASA emergency status (adjusted odds ratio, 2.11; 95% CI 2.00 to 2.23) were also independently associated with higher ASA physical status assignments. Furthermore, the model derived from the primary analysis was a better predictor of 30-day mortality than the models including either single ASA physical status or comorbidity indices in isolation (p < 0.001). We found significant correlation between ASA physical status and 27 of the 31 Elixhauser comorbidities, as well other demographic characteristics. This demonstrates the reliability of ASA scoring and its potential ability to predict postoperative outcomes. Additionally, compared to ASA physical status and individual comorbidity indices, the derived model offered better predictive power in terms of short-term postoperative mortality. Springer US 2021-07-22 2021 /pmc/articles/PMC8298361/ /pubmed/34296341 http://dx.doi.org/10.1007/s10916-021-01758-z Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Systems-Level Quality Improvement
Li, Gen
Walco, Jeremy P.
Mueller, Dorothee A.
Wanderer, Jonathan P.
Freundlich, Robert E.
Reliability of the ASA Physical Status Classification System in Predicting Surgical Morbidity: a Retrospective Analysis
title Reliability of the ASA Physical Status Classification System in Predicting Surgical Morbidity: a Retrospective Analysis
title_full Reliability of the ASA Physical Status Classification System in Predicting Surgical Morbidity: a Retrospective Analysis
title_fullStr Reliability of the ASA Physical Status Classification System in Predicting Surgical Morbidity: a Retrospective Analysis
title_full_unstemmed Reliability of the ASA Physical Status Classification System in Predicting Surgical Morbidity: a Retrospective Analysis
title_short Reliability of the ASA Physical Status Classification System in Predicting Surgical Morbidity: a Retrospective Analysis
title_sort reliability of the asa physical status classification system in predicting surgical morbidity: a retrospective analysis
topic Systems-Level Quality Improvement
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8298361/
https://www.ncbi.nlm.nih.gov/pubmed/34296341
http://dx.doi.org/10.1007/s10916-021-01758-z
work_keys_str_mv AT ligen reliabilityoftheasaphysicalstatusclassificationsysteminpredictingsurgicalmorbidityaretrospectiveanalysis
AT walcojeremyp reliabilityoftheasaphysicalstatusclassificationsysteminpredictingsurgicalmorbidityaretrospectiveanalysis
AT muellerdorotheea reliabilityoftheasaphysicalstatusclassificationsysteminpredictingsurgicalmorbidityaretrospectiveanalysis
AT wandererjonathanp reliabilityoftheasaphysicalstatusclassificationsysteminpredictingsurgicalmorbidityaretrospectiveanalysis
AT freundlichroberte reliabilityoftheasaphysicalstatusclassificationsysteminpredictingsurgicalmorbidityaretrospectiveanalysis